Publication Type
Conference Proceeding Article
Version
acceptedVersion
Publication Date
6-2012
Abstract
Viral diffusion allows a piece of information to widely and quickly spread within the network of users through word-ofmouth. In this paper, we study the problem of modeling both item and user factors that contribute to viral diffusion in Twitter network. We identify three behaviorial factors, namely user virality, user susceptibility and item virality, that contribute to viral diffusion. Instead of modeling these factors independently as done in previous research, we propose a model that measures all the factors simultaneously considering their mutual dependencies. The model has been evaluated on both synthetic and real datasets. The experiments show that our model outperforms the existing ones for synthetic data with ground truth labels. Our model also performs well for predicting the hashtags that have higher retweet likelihood. We finally present case examples that illustrate how the models differ from one another.
Keywords
Viral diffusion, Diffusion related factors, Twitter network
Discipline
Databases and Information Systems | Numerical Analysis and Scientific Computing
Publication
Proceedings of the Sixth International Conference on Weblogs and Social Media
City or Country
Dublin
Citation
HOANG, Tuan-Anh and LIM, Ee Peng.
Virality and susceptibility in information diffusions. (2012). Proceedings of the Sixth International Conference on Weblogs and Social Media.
Available at: https://ink.library.smu.edu.sg/sis_research/1546
Copyright Owner and License
LARC
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
http://www.aaai.org/ocs/index.php/ICWSM/ICWSM12/paper/viewFile/4584/4977
Included in
Databases and Information Systems Commons, Numerical Analysis and Scientific Computing Commons